A picture is worth a thousand words. Images play an important role in helping users understand the semantics or meanings of a web based textual query. This understanding enhances a user's search and web browsing experience. For example, given a textual description of a new concept or object, most people will try to imagine its appearance in their mind. Simply providing image responses to a text based query will help users understand the semantics of the query text more fully at a glance.
Commercial search engines often include images in responses to textual queries. Commonly, these responses include images that are currently most popular, part of a current trend (e.g., trending now) or associated with web based user search patterns. Unfortunately, image responses based on popularity, trends of search patterns may not best represent the actual intent of the textual query.
Other systems may leverage term categorization to find image responses associated with one or more semantic classes of a textual query. These systems often use image sets with well defined semantics identified a-priori to generate responses to textual queries. Unfortunately, these systems are limited by the pre-defined semantics, and may not provide image responses that best represent a broad array of potential textual queries.